Detection Event Log¶
Class: DetectionEventLogBlockV1
Source: inference.core.workflows.core_steps.analytics.detection_event_log.v1.DetectionEventLogBlockV1
This block maintains a log of detection events from tracked objects. For each tracked object it records: class name, first and last seen frame numbers, absolute wall-clock timestamps (Unix epoch floats derived from frame_timestamp metadata, or time.time() as fallback), and relative timestamps in seconds since the video started. Objects must be seen for a minimum number of frames (frame_threshold) before being moved from 'pending' to 'logged' status. Stale events (not seen for stale_frames frames) are removed during periodic cleanup (every flush_interval frames). When a logged event goes stale it is emitted in the complete_events output, which contains the full event data for objects that were tracked long enough to be logged and have since left the scene. The reference_timestamp parameter is deprecated and no longer used.
Type identifier¶
Use the following identifier in step "type" field: roboflow_core/detection_event_log@v1to add the block as
as step in your workflow.
Properties¶
| Name | Type | Description | Refs |
|---|---|---|---|
name |
str |
Enter a unique identifier for this step.. | ❌ |
frame_threshold |
int |
Number of frames an object must be seen before being logged.. | ✅ |
flush_interval |
int |
How often (in frames) to run the cleanup operation for stale events.. | ✅ |
stale_frames |
int |
Remove events that haven't been seen for this many frames.. | ✅ |
reference_timestamp |
float |
Deprecated, no longer used. Absolute timestamps are now taken directly from frame_timestamp metadata (or time.time() as fallback).. | ✅ |
fallback_fps |
float |
Fallback FPS to use when video metadata does not provide FPS information. Used to calculate relative timestamps.. | ✅ |
The Refs column marks possibility to parametrise the property with dynamic values available
in workflow runtime. See Bindings for more info.
Available Connections¶
Compatible Blocks
Check what blocks you can connect to Detection Event Log in version v1.
- inputs:
Object Detection Model,Perspective Correction,OCR Model,SAM 3,BoT-SORT Tracker,Detections Filter,Path Deviation,VLM As Detector,Object Detection Model,Line Counter,SAM 3,Detections Merge,Instance Segmentation Model,Detections Stabilizer,YOLO-World Model,Time in Zone,Cosine Similarity,OC-SORT Tracker,Detections Classes Replacement,Dynamic Zone,VLM As Detector,Segment Anything 2 Model,Dynamic Crop,Detections Consensus,Mask Area Measurement,Detections Transformation,Seg Preview,Time in Zone,Detections List Roll-Up,Google Vision OCR,SAM 3,Camera Focus,Instance Segmentation Model,Camera Focus,Path Deviation,Per-Class Confidence Filter,Detections Stitch,Overlap Filter,Gaze Detection,Detection Offset,Byte Tracker,PTZ Tracking (ONVIF),Identify Changes,SORT Tracker,EasyOCR,Motion Detection,Detections Combine,Bounding Rectangle,Byte Tracker,Template Matching,ByteTrack Tracker,Mask Edge Snap,Instance Segmentation Model,SAM2 Video Tracker,Byte Tracker,Moondream2,Velocity,Detection Event Log,Object Detection Model,Time in Zone - outputs:
Email Notification,Keypoint Detection Model,Path Deviation,Morphological Transformation,Twilio SMS/MMS Notification,Line Counter,Time in Zone,Stitch OCR Detections,Heatmap Visualization,Email Notification,Keypoint Visualization,Anthropic Claude,Label Visualization,Instance Segmentation Model,Path Deviation,Overlap Filter,Motion Detection,Byte Tracker,Background Color Visualization,Mask Edge Snap,Instance Segmentation Model,Polygon Visualization,Velocity,SIFT Comparison,Detection Event Log,Florence-2 Model,Grid Visualization,Time in Zone,Detections Filter,Detections Merge,Detections Stabilizer,Keypoint Detection Model,Image Preprocessing,Roboflow Dataset Upload,Dynamic Zone,Segment Anything 2 Model,Corner Visualization,Stability AI Outpainting,Halo Visualization,Time in Zone,Detections List Roll-Up,Blur Visualization,Distance Measurement,Morphological Transformation,Trace Visualization,Stitch OCR Detections,Reference Path Visualization,Halo Visualization,Model Comparison Visualization,Dot Visualization,Pixel Color Count,Background Subtraction,Text Display,Detections Combine,Bounding Rectangle,ByteTrack Tracker,Absolute Static Crop,Florence-2 Model,Byte Tracker,Icon Visualization,Identify Outliers,Mask Area Measurement,Object Detection Model,Perspective Correction,SAM 3,BoT-SORT Tracker,Stability AI Inpainting,Object Detection Model,Line Counter,QR Code Generator,Model Monitoring Inference Aggregator,Image Threshold,OC-SORT Tracker,Anthropic Claude,Dynamic Crop,Detections Consensus,Size Measurement,Dominant Color,Bounding Box Visualization,Detection Offset,Keypoint Detection Model,Image Contours,Polygon Visualization,Image Blur,Per-Class Confidence Filter,Anthropic Claude,Triangle Visualization,Object Detection Model,Roboflow Custom Metadata,SIFT Comparison,Slack Notification,Image Stack,Pixelate Visualization,Stitch Images,Instance Segmentation Model,Image Slicer,Line Counter Visualization,Image Slicer,Detections Classes Replacement,Roboflow Dataset Upload,Detections Transformation,Color Visualization,Classification Label Visualization,Camera Focus,Detections Stitch,Byte Tracker,Ellipse Visualization,PTZ Tracking (ONVIF),Identify Changes,SORT Tracker,Mask Visualization,Crop Visualization,Circle Visualization,SAM2 Video Tracker,Roboflow Vision Events,Webhook Sink,Twilio SMS Notification
Input and Output Bindings¶
The available connections depend on its binding kinds. Check what binding kinds
Detection Event Log in version v1 has.
Bindings
-
input
image(image): Reference to the image for video metadata (frame number, timestamp)..detections(Union[instance_segmentation_prediction,object_detection_prediction]): Tracked detections from byte tracker (must have tracker_id)..frame_threshold(integer): Number of frames an object must be seen before being logged..flush_interval(integer): How often (in frames) to run the cleanup operation for stale events..stale_frames(integer): Remove events that haven't been seen for this many frames..reference_timestamp(float): Deprecated, no longer used. Absolute timestamps are now taken directly from frame_timestamp metadata (or time.time() as fallback)..fallback_fps(float): Fallback FPS to use when video metadata does not provide FPS information. Used to calculate relative timestamps..
-
output
event_log(dictionary): Dictionary.detections(Union[object_detection_prediction,instance_segmentation_prediction]): Prediction with detected bounding boxes in form of sv.Detections(...) object ifobject_detection_predictionor Prediction with detected bounding boxes and segmentation masks in form of sv.Detections(...) object ifinstance_segmentation_prediction.total_logged(integer): Integer value.total_pending(integer): Integer value.complete_events(dictionary): Dictionary.
Example JSON definition of step Detection Event Log in version v1
{
"name": "<your_step_name_here>",
"type": "roboflow_core/detection_event_log@v1",
"image": "$inputs.image",
"detections": "$steps.byte_tracker.tracked_detections",
"frame_threshold": 5,
"flush_interval": 30,
"stale_frames": 150,
"reference_timestamp": 1726570875.0,
"fallback_fps": 1.0
}